Artificial Intelligence has changed the way of consuming the content by customizing it. If we see, from media to manufacturing, Artificial Intelligence plays a dominant role in creating the content more relevant and responsive for the companies.
AI is a broad term that encompasses many different goals and approaches to solving personalization goals, said by the CEO of Movable Inks, Vivek Sharma.
It is important to note that with true AI, a machine draws conclusions from data and makes decisions that a human normally would, said Sharma. When personalizing content with AI, the machine isn't confined to follow a set of human-led, marketer-defined rules, but instead analyzes all relevant available data in real time and makes decisions about what content to display based on the data.
It is believed that AI depends on both a rich dataset (volume, variety, velocity), as well as effective algorithms.
There is a direct correlation between the diversity of data used to personalize marketing content and the quality of the resulting customer experience and its possible for a small variety of data points to have a high predictive value, like an abandoned shopping cart, said Sharma. It is also possible to extrapolate from a small volume of data like looking at the behaviors of online shoppers from NYC. However, a limited dataset can reinforce learnings that aren't representative of what happens in a broader dataset. This traps us in local maxima.
Sharma says that a great example of bias is if you only drove a Tesla on racetracks, then you would lack the data on how to drive in real-world environments.
Optimizing personalized content often falls short because brands are working with biased datasets, said Sharma. Personalization is used by different companies to mean a variety of things and can even include inserting a customers name into an email, but potentially training data that can power an AI algorithm for content personalization is vast and falls into three key buckets: customer data, behavioral data, and contextual data.
According to Leila Janah, CEO and founder at Samasource, the personalization of content curated by AI comes from the data fed into the AI algorithm.
In the case of training data that lacks diversity, the AI isn't able to provide truly personalized and targeted content said Janah. The challenge is that so much of our technology is trained around a small subset of consumers and cant offer the best recommendations to the wider range of those targeted by personalized marketing efforts.
Sharma believes that AI is getting much better at personalizing content and computers are finally starting to understand what brand images are about inferring metadata from unstructured visual content
The beauty of AI is that it can study the customer and select the image and content that would most likely appeal to her or him, added Sharma. It's helping them respond to real-time events, and develop new brand experiences through design. Its also enabling brands to customize the content, which is a complement to personalization.
The more a content creator knows about their video content, as well as who is using it and how they are using it, the more easily they can sell the right advertising message to the right viewer, as said by Juan Carlos Riveiro. the more easily they can sell the right advertising message to the right viewer, said Juan Carlos Riveiro, CEO, and co-founder of Spanish startup Vilynx. As the media business shifts to become more subscription-oriented, being able to customize the experience to each user means they are more likely to sign up in the first place, watch more and stay subscribed longer.
Vilnyx uses visual recognition, natural language processing, and text analysis to understand the relationship between people, objects, and ideas in media. The startup has raised $8.4 M in funding in a total of three funding rounds and in October 2018, Jon Klein joined as president. Klein is the former president of CNN.
San Francisco-based Chooch, which raised a $2.8 M seed round in April 2019 led by Vickers Venture Partners, is an AI training platform for visual recognition in media and other industries as well.
The company says its an end-to-end, deep learning visual AI solution which can be used where visual recognition is needed such as identifying human faces or counting cancer cells. Chooch can be trained to accurately identify features in any media, such as web-based video or images on mobile phones, live drone feeds and medical imagery.
Ideally, software for personalizing content is built to actively look for and incorporate new data that can revise the models and it will also assign a greater weighting to new data that challenges existing conclusions and assume there may be more like it, said Sharma. With more diverse amounts of data from multiple sources, AI can better generate content that's optimized for every customer at scale resulting in better engagement and sales.
Janah says, that for marketing companies, biased data can have a real negative impact on the bottom line and to make the most efficient marketing tactics and understand the needs of consumers, it requires highly trained data that comes from a large and diverse data set.